1. Field
The present disclosure is generally related to a method of and system for improving storage of image data in digital printing or scanning. More specifically, the present disclosure relates to a method of and system for storing image data manipulated by mixed-raster content (MRC) segmentation processes for improved image quality.
2. Description of Related Art
Before image data is stored (and later output) to a digital output device, the image data is preferably compressed, i.e., coded to minimize the space needed to store and output the image data. In particular, due to its large size, digital image data that is output to a device such as a multi-function printer (e.g., for copying and/or printing) typically requires compression. For color or grayscale image data that is to be compressed, conversion of such image data to binary image data is generally not sufficient.
One technique for manipulating digital image data includes segmentation (or auto-segmentation). Segmenting image data into two or more planes tends to improve compression of the image, and also allows different compression methods to be applied to the different planes. For example, it is generally known in the art that a format such as mixed raster content (MRC) (also referred to as multiple raster content) may be used by digital multifunction devices (MFDs) to manipulate and compress image data. Such MRC compression models are becoming increasingly popular for image storage or archiving, especially for text documents and forms because of their increased compressibility.
In current 3-layer MRC models, for example, the generation of foreground and background planes or layers go through cleanup in a mark up edges module where certain areas in the foreground and background planes are filled with zeros (or some other value(s)) to reduce the file size. Current algorithms, however, generally do not improve image quality at this stage and restrict the cleaning of background and foreground planes to only four cases. Also, high compression ratios for noisy and halftone images may not provide a good enough image quality. For example, current algorithms may misdetect edges in such images (i.e., detect false edges).
Therefore, a method for improving output image quality as well as further reducing file sizes using MRC segmentation techniques is desirable.